Digitate, a Tata Consultancy Services venture, sells ignio for autonomous IT and business operations. After moving to SaaS, it priced about 35 capabilities across 100+ SKUs on a homegrown CPQ where each new product waited two months on engineering and half the deals bypassed the system. DealHub AI replaced it with a pricing engine wired natively into HubSpot. The pricing team now ships a new product in a week, and every quote lands in the CRM without retyping.
Digitate's pricing team ships a new product in days, not two months.
Sellers build a quote in 10 to 15 minutes, down from 30 to 45.
Quotes sync into HubSpot, so nobody retypes deal data between systems.
Digitate had built its own CPQ, and it could not keep up with the company it was built for. Adding a new product or a new price model took about two months, so by the time it went live the pricing strategy behind it had already moved on. The system also had no out-of-the-box connection to HubSpot, so only 50 to 60% of deals ever went through it. Sellers built the rest offline, retyped the details into the CRM by hand, and the operations team then compared the two records line by line before any report reached leadership. It still came out wrong often enough that leadership stopped trusting the pipeline numbers. On the pricing side the cost was simpler. A model you cannot launch inside the quarter it was designed for is a model nobody sells.
Our numbers do not reconcile between the quoting system and the CRM. Why are we still checking two records by hand before we can report a pipeline?
Nearly half our deals are being quoted outside the system we built. What is the point of a CPQ that cannot cover the scenarios our sellers actually face?
A new price model takes two months to go live and the market has moved by then. How are we supposed to price a SaaS portfolio at that speed?
Every rule change goes back to engineering. Why is a commercial decision sitting in a development queue?
| Before | After |
|---|---|
A new product or price model took one to two months to build into the in-house CPQ, by which time the market had moved. | Digitate's pricing team puts a new product or price model live in three to seven days, without writing code. |
Roughly 35 capabilities across 100+ SKUs needed an engineer to add, and the system could not validate which combinations were sellable. | One rules engine enforces the capability model, and the pricing team adds and reprices capabilities itself. |
Quotes took 30 to 45 minutes on an interface sellers found hard to navigate. | Sellers build a quote in 10 to 15 minutes from templates and automated pathways. |
Only 50 to 60% of deals went through the CPQ, and the other 40 to 50% were quoted offline and retyped into HubSpot. | 100% of deals run through the CPQ, and every quote, discount and approval syncs into HubSpot as it is made. |
Replacing the in-house system meant a migration Digitate had no internal IT resource to run. | DealHub AI configured the rules and integrations alongside the pricing team and went live in 12 to 16 weeks. |
“Commercial success for my team at Digitate means consistently growing revenue and profitability by using scalable, value-based pricing aligned with our expanding SaaS portfolio… We improve our pricing accuracy and sales efficiency via DealHub CPQ automation and data insights, supporting GTM teams with flexible terms for diverse customers.”
Kavish Shah
Commercial Lead
DealHub AI gave Digitate's pricing team one place to hold value-based pricing for an expanding SaaS portfolio. Previously, price models were built into a CPQ the company maintained itself and every change waited on engineering. Now the team builds the model, the rules and the approvals, and the data comes back clean.
Digitate's pricing team, with a DealHub AI customer success manager and solution architect working alongside.
Pricing-team-owned configuration. Price books, SKUs, configuration rules and approvals are maintained directly by the pricing team.
12 to 16 weeks from assessment to rollout, across design, configuration, testing and go-live.
Phased, with pilot launches and early rep involvement. Deal coverage moved from 50 to 60% on the in-house system to 100%.
HubSpot CRM, natively integrated, with quotes, configurations, discounts and approvals syncing in real time.
No dedicated IT resource. The pricing team administers DealHub AI itself and makes pricing and rule changes without engineering.
DealHub is ISO 27001, ISO 27701, ISO 22301, and ISO 42001 certified, holds SOC 1 Type II and SOC 2 Type II attestations, and is GDPR and CCPA compliant, alongside additional security, privacy, and compliance frameworks.
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Friction between Quote-to-Revenue
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